AI-equipped drones are changing pest control in agriculture to help reduce food waste. Researchers are now using AI to find better ways to manage pests. The University of Modena and Reggio Emilia in Italy is showing how AI can transform farming.
Revolutionizing Pest Control With AI-Equipped Drones
Using AI on drones is a new way to help farmers fight pests. With AI, farmers can more accurately target pests. One primary pest they're focusing on is the brown marmorated stink bug, which damages orchards in North America and southern Europe.
Farmers can protect their crops from these pests more efficiently using AI-equipped drones. The pest caused staggering damages in Italy, reaching nearly US$640 million in 2019.
Traditional methods like pheromone traps, visual sampling, and sweep-netting are used to combat the pest, but they're labor-intensive and impractical for large orchards.
Driven by this challenge, Interesting Engineering reported that Lara Maistrello, an associate professor in the Department of Life Sciences at the University of Modena, led a team of researchers to find more time and energy-efficient solutions.
The researchers devised an automated flight plan for drones to capture high-resolution images of pear orchards from a height of 26 feet. Drones flying at this altitude were less disruptive to pest movements than human observers.
Interestingly, adult bugs reacted by freezing when drones approached, aiding in capturing clear images of the area. These images were then utilized to train AI models to identify pest infections.
Using this data, the trained models showed higher efficiency in detecting the stink bug, achieving an accuracy of 97% compared to models trained from the beginning.
The researchers proposed applying this method to integrated pest management strategies, offering accurate predictions that can adjust to evolving environmental and weather conditions.
Environmental Sensing With Flat Optic Lenses
In another research, scientists from the City University of New York (CUNY), the University of Melbourne, RMIT University, and the ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS) tackled the hurdles of curved optical lenses in environmental sensing.
They devised a flat imaging sensor made of the thin material vanadium dioxide. In addition to its small size and lightweight, this sensor can switch between precise infrared imaging and edge detection as needed.
Madhu Bhaskaran, a professor at RMIT University's School of Engineering in Australia, explained that as the filter's temperature changes, vanadium dioxide transforms from an insulating state to a metallic one. This shift causes the processed image to transition from a filtered outline to an unfiltered infrared image.
Crucially, the sensor system can carry out these tasks at the edge, eliminating the need for extensive data storage and energy-intensive processors. The flat-optic lenses produced with this technology are lightweight, small, and consume less power. They are ideal for replacing conventional lenses in sensing applications with drones and satellites.
Experts propose that this technology could assist farmers in enhancing their crop yields by swiftly identifying the specific needs of crops instead of employing a generalized approach.
Cost savings from irrigation, pest management, and fertilizer usage could also help make groceries more affordable for consumers.
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